Industrial Monitoring

Industrial monitoring leverages advanced data analytics to enhance efficiency, safety, and predictive capabilities within manufacturing and process industries. Current research heavily emphasizes the application of machine learning, particularly deep learning architectures like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), for tasks such as anomaly detection, predictive maintenance, and fault diagnosis. These methods are applied to diverse data sources, including sensor readings, visual inspections, and alarm logs, to improve operational efficiency, reduce downtime, and enhance workplace safety. The resulting improvements in process optimization and predictive maintenance have significant implications for both economic productivity and industrial safety.